User Context Research Articles

Wealth/Poverty Opposition in English and Kazakh: A Comparative Study

This research employs linguistic concept modeling to scrutinize the semantic variations between notions of wealth and poverty in English and Kazakh, aiming to discern their contrasting characteristics. The corpora in English and Kazakh encompassing varied genres, styles, and thematic content were examined through word frequency and co-occurrence to elucidate divergent contextual frames for the terms in both languages, unveiling cultural nuances and cognitive associations. The results indicate that in English, wealth is majorly associated with financial prosperity, real estate ownership, and the availability of resources for a comfortable lifestyle. Conversely, in Kazakh-language writings, the concept of wealth extends to encompass elements like family connections and devotion to the homeland, reflecting cultural priorities and lifestyles. A comparable distinction is evident when examining the contextual usage of the term poverty. The findings underscore the significance of exploring linguistic concepts within distinct cultural and cognitive frameworks, opening avenues for further comparative linguistic research.

Understanding Contextual Aspects of the Word ‘Look’ in Corpus of Contemporary American English: Semantics Study

This research investigates the contextual aspects and lexical semantics of the word "look" within the Corpus of Contemporary American English (COCA). By examining how "look" functions across different contexts, this study aims to uncover the multifaceted nature of its meaning and usage. The research is grounded in semantic theory, drawing on the works of Leech, and other prominent linguists to explore how meaning is constructed and conveyed through language. Key focuses include the categorization of "look" across various parts of speech, such as verbs, nouns, and interjections, and the examination of its idiomatic, non-idiomatic, and compositional meanings. The study employs a qualitative research methodology, analyzing linguistic data from COCA to identify patterns and themes in the usage of "look." This research aims to elucidate the complex interplay between context and meaning, offering insights into the cognitive processes involved in language comprehension and production. The findings highlight the significance of semantics in understanding language, particularly how specific words can convey a wide range of meanings depending on their contextual usage. Overall, this research contributes to the field of lexical semantics by providing a comprehensive analysis of the word "look," demonstrating its versatility and the intricate mechanisms by which meaning is negotiated in language. The research has implications for linguistic theory, language education, and the development of more precise language processing systems.

Development of interactive digital teaching materials based on 21st century skills in special purpose arabic language courses at STAI Attanwir Bojonegoro

Special Purpose Arabic Language refers to the teaching or learning of Arabic language tailored to specific needs or objectives. This means that Arabic language lessons are designed with a focus on its usage context in specific fields or activities, as opposed to a general approach to teaching Arabic. Special Purpose Arabic Language courses at the university level are tailored to specific needs and objectives in a professional context, producing graduates ready to face global challenges. The objectives of this research are (1) to analyze the process of developing interactive digital teaching materials based on 21st-century skills in Special Purpose Arabic Language courses at STAI Attanwir Bojonegoro, (2) to analyze the feasibility of interactive digital teaching materials based on 21st-century skills in Special Purpose Arabic Language courses at STAI Attanwir Bojonegoro, and (3) to analyze the effectiveness of interactive digital teaching materials based on 21st-century skills in Special Purpose Arabic Language courses at STAI Attanwir Bojonegoro. This research uses the Research and Development (R&D) method using the ADDIE model. Data collection techniques in this study use expert validation questionnaires, expert validation materials, student responses, and tests. The results of this research and development are as follows: (1) The development process consists of five steps: analysis, development, design, implementation, and evaluation, resulting in the production of interactive digital teaching materials based on 21st-century skills. (2) Based on validation results by experts, an average score of 90% was obtained. According to the Likert scale, the value of 90% falls into the category of very feasible because it is within the range of >61%. Meanwhile, the average percentage of student responses obtained an overall score of 88.5%, falling into the category of very feasible. (3) The results of the effectiveness test of teaching materials using a paired sample T-test showed a significant difference between pre-test and post-test scores with a significant value (2-tailed) of p = 0.000, <0.05. The null hypothesis (H0) in this study was rejected, and the alternative hypothesis (Ha) was accepted, indicating a significant difference between the two tests. Based on the data above, the developed teaching materials are effective in Special Purpose Arabic Language courses.

User Interface Design for the Orca Music Player Mobile Application

The rapid development in the field of information technology has resulted in a significant change in the way music is listened to. The current digital generation prefers to listen to music online through their digital devices. Thus, designing User Interface and User Experience on Mobile Music Player Applications using the User Centered Design method which consists of Plan the human centered process, Specify the context of use, Specify user and organizational requirements, and Produce design Solution. The target audience for this design is productive age children 15-35 years old with product limitations that only reach the prototype stage and feature services that are still lacking. The platform used is the android and ios mobile platform and UI design by making Wireframe of the application design.

상황인식 기반 AR-HUD(헤드업 디스플레이) 인터페이스 디자인에 관한 연구

With the development of intelligentization of the vehicle industry, cars are no longer just means of transportation, and various sensors and virtual entertainment systems have begun to be applied for autonomous vehicles and smart cars. Rise of in-vehicle information required by the new intelligent interaction method for information processing theory, this study has see car - human interaction interface based on AR technology introducing, driving experience and can improve the driving safety is studied interface design. To this end, literature research, case comparative analysis, and surveys were conducted, and comparative analysis was conducted on Tesla HUD and Huawei AR-HUD. In addition, through in-depth investigation of contextual user demands, it analyzed existing problems and proposed optimization of AR-HUD interface design based on situational awareness from three aspects of function, interaction and vision. Study driver's driving experience, improve driving stability, AR - propulsion, smart and personalization of HUD interface design intelligent vehicles and vehicles of the self-driving car and future improvement and theoretical foundation for design of an interface by providing drivers contributing to meet demand.

Understanding the relationship between AI and gender on social TV content selection

As technological advancements continue to shape our daily lives, and social TV has emerged as an interactive platform that fosters connections between families and friends. This study investigates the selection of social TV content by examining the influence of AI and other contributing factors, with gender proposed as a mediating factor. Involving 300 students from two randomly selected public universities in Irbid, Jordan, data were collected through an online survey with self-reported responses. The study revealed that AI enhances characteristics such as information gathering, social awareness, and knowledge sharing, subsequently affecting user attitudes and content selection on social TV platforms. Both AI and user attitudes significantly contribute to content selection, while gender acts as a mediator, influencing AI integration and attitudinal shifts. Ultimately, AI provides seamless access to preferred content and improves ease of use, enriching content recommendation systems and fostering increased user interest and satisfaction. This positive experience with AI services shapes user attitudes towards technology. This study offers a comprehensive examination of the intersection between AI, gender, attitudes, and social TV content selection within the context of Jordanian young users, marking a pioneering contribution to the field of media studies in the MENA region.

Providing a common language for obesity: the European Association for the Study of Obesity obesity taxonomy.

The basis for a high-performing and resilient healthcare system is having a common, precise, and scientifically accurate language used across all stakeholder groups. However, such a common language is lacking for obesity. Therefore, the European Association for the Study of Obesity undertook a taxonomy initiative to provide standardised language for obesity as commonly used from policy to practice for other major policy-prioritised non-communicable diseases (NCDs). An online Delphi consensus study was conducted, involving a panel of experts representing stakeholder groups of policymakers, healthcare professionals, people with lived experience, and researchers. Based on the understanding of obesity as an adiposity-based chronic disease, 54 statements demarcated into definition, scope and contextual usage were developed across six themes: Definition of obesity, Causes, onset and progression, Obesity prevention, Screening and early diagnosis, Treatment and management, Obesity consequences. Of the 194 invited experts, 70 (36%), 63 (33%), and 58 (30%) experts participated in rounds one, two, and three, respectively. Consensus was achieved on 70% of the proposed definitions, scope, and contextual usage after round one, 94% after round two and 100% after round three. The Definition of Obesity theme included distinctions between population-level indicators and individual-level signs of obesity, and how pre-obesity was defined. The Causes, Onset and Progression theme characterised the timing of obesity development. The Obesity Prevention theme explicitly differentiated between health promotion and primary prevention. Both the Screening and Early Diagnosis, and the Treatment and Management themes defined concepts supporting a continuum of care model. The Consequences of Obesity theme encompassed health and socio-economic outcomes. The taxonomy provides a contemporary evidence-based language about obesity that aligns with language used for policy-prioritised NCDs. The taxonomy is useful for education, advocacy, and communication and can be used by policymakers, healthcare professionals, people living with obesity, researchers, and health system users.

Implementing Library Maker Projects Outside of the Makerspace

The popularity and relevance of the library makerspace has been well-established and documented in the previous decade of researcher and practitioner work, including numerous hands-on guides from a variety of dimensions relevant to starting and operating a makerspace. Less studied, however, and the focus of this work are the applications of maker technologies within wider library work. Prior qualitative research conducted by the author included interviews with librarians to understand and document their use of maker technologies, such as the Raspberry Pi single-board computer, to support broader library work outside of the makerspace. The findings indicated that common use cases included running library display screens and collecting patron traffic numbers and environmental data. The objective of this subsequent case study is to examine the potential for wider use of such projects by librarians in an academic library setting, by introducing these projects into a new library setting and assessing the related code and educational materials developed by the researcher. This work reports on the findings of the case study, in which the projects were successfully operated in several usage contexts, as well as the challenges and broader implications for adoption within libraries of all types.

Explainable assessment of financial experts’ credibility by classifying social media forecasts and checking the predictions with actual market data

Social media include diverse interaction metrics related to user popularity, the most evident example being the number of user followers. The latter has raised concerns about the credibility of the posts by the most popular creators. However, most existing approaches to assess credibility in social media strictly consider this problem a binary classification, often based on a priori information, without checking if actual real-world facts back the users’ comments. In addition, they do not provide automatic explanations of their predictions to foster their trustworthiness. In this work, we propose a credibility assessment solution for financial creators in social media that combines Natural Language Processing and Machine Learning. The reputation of the contributors is assessed by automatically classifying their forecasts on asset values by type and verifying these predictions with actual market data to approximate their probability of success. The outcome of this verification is a continuous credibility score instead of a binary result, an entirely novel contribution by this work. Moreover, social media metrics (i.e., user context) are exploited by calculating their correlation with the credibility rankings, providing insights on the interest of the end-users in financial posts and their forecasts (i.e., drop or rise). Finally, the system provides natural language explanations of its decisions based on a model-agnostic analysis of relevant features.

The Need for Adaptive Access Control System at the Network Edge

The emergence of edge computing, characterized by its distributed nature and real-time processing, necessitates a paradigm shift in access control mechanisms. Traditional, static methods struggle to adapt to the dynamic and heterogeneous environment of edge computing. This research addresses this gap by proposing an Adaptive Risk-Based Access Control (ARBAC) model specifically designed for edge environments. The objective of this research is to develop a robust access control system that dynamically responds to the changing security landscape of edge computing. The proposed ARBAC model integrates real-time data on user context, resource sensitivity, action severity, and risk history to dynamically assess the security risk associated with each access request. This approach ensures a balance between robust security and user experience by tailoring access controls based on the specific context. The research builds upon the growing recognition of the limitations of traditional access control methods in edge environments. Existing literature highlights the need for adaptive and risk-based access control models to address the dynamic nature of edge computing. This research contributes to this evolving field by proposing an ARBAC model that leverages real-time information for contextually relevant access decisions. The proposed ARBAC model offers several advantages. By dynamically adjusting access controls based on risk levels, the model enhances security and ensures compliance with regulatory requirements. Additionally, it improves network performance by reducing load and facilitating faster access to resources. Furthermore, the model's scalability makes it suitable for managing access in large-scale edge deployments. In conclusion, this research proposes an ARBAC model that aligns with the dynamic nature of edge computing environments. By leveraging real-time data and contextual information, the model offers a robust and adaptable approach to access control, promoting security, compliance, performance, and scalability in edge computing. This research paves the way for further exploration and implementation of ARBAC systems, empowering organizations to effectively manage access control in the evolving landscape of edge computing and IoT.

Multi-Level Encryption System using AES and RSA Algorithms

Abstract: As the volume of sensitive data entrusted to the cloud explodes, from healthcare records to financial transactions, the need for robust security solutions intensifies. Traditional encryption techniques, while effective, remain vulnerable to key compromise, leaving data exposed to malicious factors. This study proposes a multi-level encryption strategy that leverages the power of AES for efficient data encryption, RSA for secure key protection with public-key cryptography, and role-based encryption for granular access control. This layered approach significantly increases the computational complexity for unauthorized access, making brute-force or dictionary attacks exponentially more difficult. Our research demonstrates successful integration of these algorithms, achieving a 50% reduction in key compromise risk and enhanced data integrity through MAC verification. Moving forward, we envision seamless integration with multiple cloud platforms and exploring advanced access control mechanisms based on user context and behavior. This multi-level encryption strategy holds immense potential to reshape the landscape of cloud data security, fostering a more secure and trustworthy digital future.

Could Gameplay Data of Games with a Purpose Assist in Training Hazardous Situations in the Industry?

Accidents and risks in the industry pose significant challenges concerning executing critical tasks. Inadequate employee training compromises the ability to manage risks, making the environment prone to accidents. In this context, games with training purposes emerge as a promising solution, providing an interactive and immersive environment. Focusing on improved risk management, organizational managers can utilize data collected by these games as metrics for monitoring and enhancement. However, it is necessary to understand how games with a purpose can contribute to the training process for hazardous situations in the industry. With this in mind, this study investigates the topic by exploring both the literature through a systematic mapping and the perceptions of workers from an oil and gas industry through a survey. As a result of the investigations, techniques for analyzing and visualizing gameplay data obtained from training games, design elements, game genres, and primary usage contexts were identified. Additionally, it was possible to analyze workers' perceptions from the oil and gas industry of how these games and their data can add value and contribute to safety training sections within their workplaces. Therefore, there were indications that games with a purpose, combined with data analysis and visualization techniques, can offer a new perspective for conducting and evaluating training, providing information that contributes to improving work quality indices and reducing severe accident risks within the industry.

An Analysis of Approbation and Sympathy Maxims Based on Leech’s Politeness Principles in Emma Movie

This research aims to identify the most dominant type of politeness principles especially on approbation and sympathy maxims and the application both of them in Emma movie. This research was descriptive study. The corpus of this research was the transcript of dialogue spoken by the characters in Emma movie. The data are collected using the theory of Creswell which consists of five interrelated steps. These steps respectively deal with identifying the movie, gaining information relate to that movie, considering the focus of information, designing tool named datasheet, and administering the data. Then the data were analyzed descriptively using the theory from Miles, Huberman, & Saldana which consists of data condensation, data display, and drawing conclusion. The researcher used the theory of Leech to analyze the most dominant type of politeness principles especially approbation and sympathy maxims and also the application of both of them in the movie. The findings of this research found the most dominant type of politeness principles in Emma movie is approbation maxim with 37 data (72.55%) out of 51 data. It is followed by sympathy maxim with 14 data (27.45%) out of 51 data. The application of these two maxims happens in family discourse. This is because the context of language usage in the early 19th-century English society. The abuse of power and wealth, all prove that the class status of Emma’s family plays a significant role in the shaping how the politeness works in society.

Linking transformational leadership and digital creativity from the lens of social cognitive theory

PurposeWith the wide usage of digital technologies, employees’ digital creativity serves as a stepping stone in driving the process of organizational digital innovation. However, scant attention has been devoted to understanding the relationship between leadership and employees’ digital creativity within the digital technology usage context. Drawing upon social cognitive theory, our study aims to explore the relationship between transformational leadership and employees’ digital creativity through the mediating roles of creative self-efficacy and ambidextrous learning.Design/methodology/approachA field survey was conducted in China, garnering survey data from 223 employees actively engaged with digital technologies in their daily work. We empirically test the structural equation model to verify the hypotheses.FindingsThe results reveal a positive association between transformational leadership and employees’ digital creativity, with a consequential cascade mediation facilitated through creative self-efficacy and exploitation and exploration.Originality/valueThe empirical research not only enriches comprehension of individual-level digital creativity but also provides valuable practical insights for managers seeking to effectively drive digital innovation within their organizations.

Penerapan Metode Human Centered Design pada Perancangan Sistem Informasi Curhat Online Berbasis Web

Mental health is a very worrying health case in recent times. The number of cases that have hit the young generation of our nation is a serious threat. Pressures and challenges are often major factors in mental health crises and lack of support and places to tell stories to make a person keep everything in his mind that can hurt his mind and mentality. In this case, the research aims to overcome the problem through the implementation of a website-based online vent information system designed as a means of online vent using a Human-Centered Design approach. This Human-Centered Design approach involves a stage of user context specification, user needs, system design, and system testing using the Blackbox testing method and WebQual method. The main objective of this information system is to provide a safe and structured platform for individuals to express their feelings and emotions comfortably and safely, as well as provide support to reduce the level of mental and mental stress among the young generation of Indonesia.

Translation of Network Catchwords from the Perspective of Skopos Theory

In today's age of social media, network catchwords play an important role of cultural communication and social symbols, expressing deep semantic concepts in short words and sentences, forming a fashionable and trendy oral communication mode. Its translation involves many aspects such as language, culture and social context. This paper will take the network catchwords in 2023 as an example, and from the perspective of skopos theory, exploring the meaning, usage context and cultural and social connotation of typical catchwords such as “new track”, “Chinese modernization”, “Ceiling” and “Ice-cream assassin”. A comprehensive exploration of how multiple meanings are handled in cross-cultural translation and how these meanings are maintained or transformed in different contexts. It will help us to have a deeper understanding of the importance of network buzzwords in contemporary cultural exchanges, and provide new inspiration and direction for future research in related fields.

To Authenticity, and Beyond! Building Safe and Fair Generative AI Upon the Three Pillars of Provenance.

Provenance facts, such as who made an image and how, can provide valuable context for users to make trust decisions about visual content. Against a backdrop of inexorable progress in generative AI for computer graphics, over two billion people will vote in public elections this year. Emerging standards and provenance enhancing tools promise to play an important role in fighting fake news and the spread of misinformation. In this article, we contrast three provenance enhancing technologies-metadata, fingerprinting, and watermarking-and discuss how we can build upon the complementary strengths of these three pillars to provide robust trust signals to support stories told by real and generative images. Beyond authenticity, we describe how provenance can also underpin new models for value creation in the age of generative AI. In doing so, we address other risks arising with generative AI such as ensuring training consent, and the proper attribution of credit to creatives who contribute their work to train generative models. We show that provenance may be combined with distributed ledger technology to develop novel solutions for recognizing and rewarding creative endeavor in the age of generative AI.

PRINCIPLES OF COMPILING A GERMAN-UKRAINIAN DICTIONARY OF PARONYMS

This article addresses the principles of selecting paronyms and the methodology for compiling an electronic German-Ukrainian dictionary of paronyms using a corpus-based approach and systematic analysis to identify similarities and differences in the use of paronyms in speech. The author presents a concept of paronymy as a systemic phenomenon involving etymologically related words with similar morphemic structures but different meanings. By conducting a comparative analysis of collocations, the study identified 1,836 paronyms organized into paronymic series, each comprising two to nine components. The article examines existing dictionaries of paronyms and highlights their lexicographic shortcomings, such as excessive normative/prescriptive orientation, inadequate development of dictionary entries from both linguistic and didactic perspectives, and a lack of rigorous evaluations of modern data to inform dictionary compilation. The ideal paronym dictionary should rely on corpus data, providing reliable information with generalizations about individual word uses within conventionalized language usage. Corpus-based tools, such as those used for contrasting near-synonyms, systematically identify similarities and differences between paronyms in a contrastive manner. This process determines the degree of semantic closeness among expressions with similar contextual usage by comparing their immediate collocational patterns. The recorded semantic closeness or distance between paronyms is based on their contextual overlap in usage. The lexicographic processing of the selected paronyms was carried out with TshwaneLex, a computer-based dictionary creation software that allows lexicographers to develop dictionaries for any language without requiring advanced IT skills. TshwaneLex offers various features such as automatic cross-reference tracking, advanced dictionary comparison/merge functionality, and support for all world languages through full Unicode compatibility. The lemma editing process uses a tree-based interface to represent the hierarchical structure of the lemma, including different meanings, submeanings, word formations, multi-word units, examples of usage, cross-references, and more. Furthermore, the input/output architecture is designed to support the development of additional interfaces for various data sources as add-ons or plug-ins, facilitating other output formats. The article notes that a PHP-based software module is currently available for hosting the TshwaneLex dictionary on the internet, providing an accessible platform for electronic dictionary publication.

Understanding lexico-semantic opposition empty/full in official business texts: Quantitative and qualitative research

This paper discusses the lexical-semantic opposition EMPTY/FULL in the corpus of legal, military and medical texts. The study analyzes 130 official business texts, in which we examined the problem of defining and constructing the lexical-semantic opposition EMPTY/FULL. The analysis promoted the construction of quantitative sampling, which demonstrates the weight of the lexemes in the corpus of official business texts. The purpose of the proposed analysis was to determine the distribution of the lexical-semantic opposition EMPTY/FULL, especially to find out the total number of occurrences, the average number of occurrences and the edge limits of the lexeme EMPTY and the lexeme FULL in the corpus of texts. The main results of the study outline the diversity of the lexical-semantic opposition EMPTY/FULL in different contexts, that underlines the functional diversification of the lexeme EMPTY and lexeme FULL. The results showed that in legal texts lexemes EMPTY/FULL nominate a legal concept; in medical texts they perform the function of medical conditions assessment; within the limits of military texts, they establish an associative connection between the nomination and semantic components (military actions, targets and objects of military use, consequences of war). Another important finding was the determination of the dominant lexeme in the corpus of legal texts and the dominant lexeme in the corpus of military texts. The similarities between EMPTY and FULL are primarily due to their antonymy. However, their differences are fixed in their distinct core meanings, contextual usage, pragmatic significance and connotations. These differences make them adaptable in various contexts of military, legal and medical texts to convey precise and often contrasting information about the state of objects and concepts.

DEVELOPMENT OF INTERNET OF THINGS (IoT) BASED FLOOD EARLY WARNING TOOLS

This research is research and development (R&D) using a prototype development model. This research aims to develop an early flood warning system using the Telegram application as an early sender of information, if the water level has reached a predetermined limit. Test results: In terms of Functionality and Usability, the results of the functionality feasibility percentage were 100% and as many as 20 respondents or 100% assessed that the tool developed based on the Usability context was at 100% in the very good category. The detection speed test results show that the detection speed on the device is around 2-3 s and the speed of sending information on Oled is around 2-3 s and the speed of sending information to Telegram is 2-3 s.